Implementation of an airline recovery model in an event-based simulation

Abstract

Airlines maximize the use of their resources by minimizing the time between consecutive flight legs in their aircraft and crew schedules. As a result, bad weather or unscheduled aircraft maintenance events can have a significant impact on an airline's operations. The consequences of these disruptions are major costs to airlines, passengers and, ultimately, to the economy itself. In this thesis, the steps taken to implement an airline schedule recovery model in a realistic simulation of the U.S. airspace system are presented. The MIT Extensible Network Simulation (MEANS), an event based queueing model of the U.S. National Airspace System, can be used for tactical decision making, long term decision making and post priori event analysis. Thus, the addition of a recovery model is critical to obtain accurate simulation results. The airline recovery model consists of an optimized aircraft re-scheduling model, a crew re-assigning model and a heuristic passenger itinerary search model. The model was used to simulate airline recovery procedures over the course of a day of operations for different scenarios.